Beam-former and combiner for a multiple-antenna system

ABSTRACT

A compensating correction value for adjusting analog signals received from multiple antenna elements takes into account the effects of colored noise, co-channel interference, and inter-sample interference. The method of generating the compensating correction value for analog combining architectures considers the total channel impulse response over a block of time.

[0001] Some wireless systems use a single antenna for transmission andreception while some products incorporate multiple antennas, but use themultiple antennas in a very simple way. For instance, some smart-antennasystems incorporate selection diversity, where a switch chooses one oftwo antennas based on which antenna has a higher received signal power.

[0002] For smart-antenna systems there is a continuing need for betterways to control multiple antenna.

BRIEF DESCRIPTION OF THE DRAWINGS

[0003] The subject matter regarded as the invention is particularlypointed out and distinctly claimed in the concluding portion of thespecification. The invention, however, both as to organization andmethod of operation, together with objects, features, and advantagesthereof, may best be understood by reference to the following detaileddescription when read with the accompanying drawings in which:

[0004]FIG. 1 illustrates features of the present invention forcontrolling the gain and phase of signals in a receive chain that may beincorporated into a wireless communications device;

[0005]FIG. 2 illustrates a flow diagram for an embodiment that generatesa channel matrix H in accordance with the present invention;

[0006]FIG. 3 illustrates a flow diagram for an embodiment that includesan averaging step after the formation of the channel matrix H inaccordance with the present invention;

[0007]FIG. 4 illustrates a flow diagram for an embodiment that accountsfor colored noise in accordance with the present invention;

[0008]FIG. 5 illustrates a flow diagram for an embodiment that reducesco-channel interference in accordance with the present invention; and

[0009]FIG. 6 illustrates a flow diagram for an embodiment using SpatialDivision Multiple Access (SDMA) that incorporates analog combining inaccordance with the present invention.

[0010] It will be appreciated that for simplicity and clarity ofillustration, elements illustrated in the figures have not necessarilybeen drawn to scale. For example, the dimensions of some of the elementsmay be exaggerated relative to other elements for clarity. Further,where considered appropriate, reference numerals have been repeatedamong the figures to indicate corresponding or analogous elements.

DETAILED DESCRIPTION

[0011] In the following detailed description, numerous specific detailsare set forth in order to provide a thorough understanding of theinvention. However, it will be understood by those skilled in the artthat the present invention may be practiced without these specificdetails. In other instances, well-known methods, procedures, componentsand circuits have not been described in detail so as not to obscure thepresent invention.

[0012] In the following description and claims, the terms “coupled” and“connected,” along with their derivatives, may be used. It should beunderstood that these terms are not intended as synonyms for each other.

[0013] Rather, in particular embodiments, “connected” may be used toindicate that two or more elements are in direct physical or electricalcontact with each other. “Coupled” may mean that two or more elementsare in direct physical or electrical contact. However, “coupled” mayalso mean that two or more elements are not in direct contact with eachother, but yet still co-operate or interact with each other.

[0014]FIG. 1 illustrates features of the present invention that may beincorporated into a wireless communications device 10. The transceiverreceives and transmits modulated signals from multiple antenna. In areceiver 12, a first receiver chain includes a Low Noise Amplifier (LNA)and Variable Gain Amplifier (VGA) 16 to amplify the received signal fromantenna 14 followed by a phase shifter 18. A Digital-To-Analog Converter(DAC) 20 is connected to LNA 16 and phase shifter 18 to adjust the gainand the phase of the received modulated signal. A mixer circuit 32receives the modulated signals in the first receiver chain andtranslates the carrier frequency of the modulated signal,down-converting the frequency of the modulated signal in the receiver.The down-converted signal may be filtered through a filter 34 andconverted to a digital representation by an Analog-To-Digital Converter(ADC) 36.

[0015] Receiver 12 may further include a second receiver chain toreceive a signal from antenna 24 that includes a LNA and VGA 26,followed by a phase shifter 28. A DAC 30 is connected to LNA 26 andphase shifter 28 to adjust the gain and the phase of the modulatedsignal received in the second receiver chain. A mixer circuit 32receives the modulated signals in the second receiver chain anddown-converts the frequency of the modulated signal. The down-convertedsignal may be filtered through a filter 38 and converted to a digitalrepresentation by an ADC 40.

[0016] A baseband and application processor 68 is connected to ADCs 36and 40 to provide, in general, the digital processing of the receiveddata within communications device 10. Note that wireless communicationsdevice 10 may operate in a variety of channel conditions where thesignals received at the antenna may be corrupted by multiple propagationpaths. For instance, pedestrian or vehicular motion induces Dopplerfrequency shifts on multi-path components, resulting in a time variationof the faded multi-path channel. Thus, a wireless receiver may seemultiple signals arriving at the same time, where the signals have beenreflected off surfaces and not received in a direct path from thetransmitter.

[0017] Processor 68 may process the digitized quadrature signals, i.e.,the in-phase “I” signal and the quadrature “Q” signal from the firstreceiver chain, to provide the control signals to DAC 20 to mitigate theeffects of channel multi-path in accordance with features of the presentinvention. Likewise, the digitized quadrature signals from the secondreceiver chain are processed to provide the control signals to DAC 30 tomitigate the effects of channel multi-path in that channel.

[0018] Note that cellular communications systems may also receivesignals having interference between adjacent pulses of a transmittedcode. The distortion may be manifested in the temporal spreading andconsequent overlap of individual pulses causing the receiver difficultyin reliably distinguishing between individual signal elements. Processor68 may process the digitized quadrature signals from the first andsecond receiver chains to mitigate the effects of Inter-SymbolInterference (ISI) in accordance with features of the present invention.

[0019] The transceiver also includes a transmitter 72 where digital datareceived from processor 68 may be converted to an analog signal by aDigital-to-Analog Converter (DAC) 64. In a first transmitter path, theanalog signal may be modulated by a frequency upconverter 60, with thephase and gain of the modulated signal adjusted by a phase shifter 44and Variable Gain-Power Amplifier (VGA-PA) 42. A DAC 48 uses controlsignals from processor 68 to set a phase and signal strength that areappropriate for the modulated signal transmitted from antenna 14. In asecond transmitter path, the analog signal may be modulated by afrequency upconverter 62, with the phase and gain of the modulatedsignal adjusted by a phase shifter 54 and VGA-PA 52. Likewise, a DAC 58uses control signals from processor 68 to set a phase and signalstrength that are appropriate for the modulated signal transmitted fromantenna 24.

[0020] Receiver 12 and transmitter 72 may be embedded with processor 68as a mixed-mode integrated circuit, or alternatively, the transceivermay be a stand-alone Radio Frequency (RF) integrated circuit.Accordingly, embodiments of the present invention may be used in avariety of applications, with the claimed subject matter incorporatedinto microcontrollers, general-purpose microprocessors, Digital SignalProcessors (DSPs), Reduced Instruction-Set Computing (RISC), ComplexInstruction-Set Computing (CISC), among other electronic components. Inparticular, the present invention may be used in smart phones,communicators and Personal Digital Assistants (PDAs), medical or biotechequipment, automotive safety and protective equipment, and automotiveinfotainment products. However, it should be understood that the scopeof the present invention is not limited to these examples.

[0021] Further, the principles of the present invention may be practicedin wireless devices that are connected in a Code Division MultipleAccess (CDMA) cellular network and distributed within an area forproviding cell coverage for wireless communication. Additionally, theprinciples of the present invention may be practiced in Wireless LocalArea Network (WLAN), Wide Area Network (WAN), Personal Area Network(PAN) and Local Area Network (LAN), among others.

[0022] A memory device 70 may be connected to processor 68 to store dataand/or instructions. In some embodiments, memory device 70 may bevolatile memories such as, for example, a Static Random Access Memory(SRAM), a Dynamic Random Access Memory (DRAM) or a Synchronous DynamicRandom Access Memory (SDRAM), although the scope of the claimed subjectmatter is not limited in this respect. In alternate embodiments, thememory devices may be nonvolatile memories such as, for example, anElectrically Programmable Read-Only Memory (EPROM), an ElectricallyErasable and Programmable Read Only Memory (EEPROM), a flash memory(NAND or NOR type, including multiple bits per cell), a FerroelectricRandom Access Memory (FRAM), a Polymer Ferroelectric Random AccessMemory (PFRAM), a Magnetic Random Access Memory (MRAM), an OvonicsUnified Memory (OUM), a disk memory such as, for example, anelectromechanical hard disk, an optical disk, a magnetic disk, or anyother device capable of storing instructions and/or data. However, itshould be understood that the scope of the present invention is notlimited to these examples.

[0023]FIGS. 2-6 illustrate flow diagrams for different methods used incomputing weights for a multiple-antenna system in accordance with thepresent invention. The weights may also be referred to as antennaweights and affect the signal gain and signal phase in the receiverchains connected to the various antenna. The weights may be digitallycomputed by processor 68 for the linear combiner in receiver 12 and thebeam-former in transmitter 72. These weights take into account thetime-domain signal and the entire channel impulse response and are usedby wireless communications device 10 to improve the ratio of averagesignal power to average noise power. Accordingly, phase shifting andgain amplification may be performed on the multiple receive signalsprior to combining, with the weights for the linear combiner supplied toDACs 20 and 30. Additionally, phase shifting and gain amplification maybe performed on the multiple transmit signals prior to transmission,with the weights for the beam-former supplied to DACs 48 and 58. Notethat the weight precision may be controlled by the number of DAC bits.

[0024] Channel estimation may be performed in wireless communicationsdevice 10 by averaging over a series of known training or preamblesequences. Known symbols may be sent to receiver 12 to derive acompensating correction value that may be applied to the receiver chainthat corresponds to each antenna element. Note that the channel impulseresponse may be estimated either in the time-domain or in thefrequency-domain, where the choice of domain depends on the wirelesssystem being enhanced. By taking into account time-domain transmit orreceive signals when computing the weights, these weights may be appliedto time-domain, analog signals. In this way, these operations may beperformed with analog components and reduce the silicon hardware costs.

[0025] Referring specifically to FIG. 2, the effects of the channel onthe signals received by antenna 14 and 24 may be estimated, with thedigitized quadrature signals supplied to processor 68 for each receivechain (Process 210). The channel matrix is then formed (Process 220),where the rows of the channel matrix H are simply the channel estimates.The length of the channel estimates may be chosen to be the same for allantenna elements, although this is not a limitation of the presentinvention. Once the channel matrix has been formed, a new matrix H maybe computed (Process 230) by multiplying the matrix H with its conjugatetranspose H*, this mathematical operation being denoted as H=HH*. TheSingular Value Decomposition (SVD) algorithm may then be performed onthis matrix (Process 240), and the eigenvector corresponding to themaximum singular vector may be computed (Process 250). These weights maybe shown to be optimal in terms of maximizing the signal-to-noise powerratio for multiple analog signals. These weights computed by processor68 may be transferred to receiver 12 and used to control DACs 20 and 30(Process 260).

[0026] The transmit beam-former weights used in transmitter 72 may becomputed in the same fashion. In fact, the channel matrix may be thesame in both the transmit and receive directions, and in this case, thesame weights may be applied at both transmitter 72 and receiver 12.These weights may be used to control DACs 48 and 58 in transmitter 72 toimprove the signal-to-noise power ratio at the receiver. Referring toFIG. 3, the channel associated with each of the multiple-antenna may beestimated and a compensating correction value derived. The digitizedquadrature signals for each receive chain may be supplied by receiver 12to processor 68 (Process 310). The weights may be computed in an averagesense by adding an averaging step after the formation of the matrix H(Process 320). In this embodiment, the matrix H may be averaged over anumber of channels to obtain a new average matrix “Ha” (Process 330).This channel covariance matrix Ha may then used for SVD computation(Process 340) and weight extraction (Process 350). These weightscomputed by processor 68 may be transferred to receiver 12 and used tocontrol DACs 20 and 30 (Process 360). This scheme may be used when theexact channel is not known but the channel covariance is known.

[0027] Referring to FIG. 4, the weights to compensate for the channelmay be computed in the presence of colored noise by adding a chain ofsteps, where the colored noise is estimated in the absence of any signal(Process 410). A noise matrix K may be formed (Process 420), and a newmatrix may be computed by multiplying the matrix K with a conjugatetranspose K* (Process 430). The square root of the new matrix may thenbe computed and denoted by the matrix I, with the inverse of matrix Lthen computed (Process 440). In the original sequence of steps (Process210, 220), a step may be added after the formation of the matrix H,where the matrix H is pre and post-multiplied by the inverse of thematrix L (Process 450). The weights may then be computed using the SVDalgorithm (Process 460), just as in the non-colored noise case. Theseweights computed by processor 68 may be transferred to receiver 12 andused to control DACs 20 and 30 (Process 470).

[0028] Referring to FIG. 5, the weights used to control DACs 20 and 30may be computed to reduce the presence of co-channel interference and/orco-channel users. The interference plus noise is estimated in theabsence of any signal (Process 510) and a noise plus interference matrixO is formed that accounts for the noise and interference (Process 520).Many similarities exist between FIGS. 4 and 5. However, this matrixreduces to a special case of colored noise where the interference plusnoise is treated as colored noise. Note that the SVD algorithm is notneeded and that sub-optimal iterative algorithms, such as the iterativepower method that only compute the optimal eigenvector may be used toreduce digital complexity and computation time (Process 560). Note thatthe SVD algorithm may be replaced using matrix inverses. These weightscomputed by processor 68 may be transferred to receiver 12 and used tocontrol DACs 20 and 30 (Process 570).

[0029]FIG. 6 illustrates a flow diagram for an embodiment using SpatialDivision Multiple Access (SDMA) that incorporates analog combining inaccordance with the present invention. SDMA is a communications modethat optimizes the use of radio spectrum and uses directional propertiesof antennas. In SDMA, also known as Spatial-Division Multiplex (SDM),highly directional antennas transmit signals, allowing duplicatefrequencies to be used.

[0030] The weights or the compensating correction value used to controlDACs 20 and 30 (FIG. 1) may be computed to reduce the presence of userinterference in a SDMA network. The user interference as measured in thequadrature signals (Process 510) is used to form a matrix T (Process620). A new matrix is formed by multiplying the matrix T with theconjugate transpose T* (Process 630). The square root is taken and thematrix U is formed, then the inverse of the matrix U is taken (Process640). Process 650 defines a pre and post multiplying of the matrix H bythe inverse of the matrix U. These weights computed by processor 68 maybe transferred to receiver 12 and transmitter 72 to control DACs 20 and30 (Process 670).

[0031] In general, all of these embodiments described in FIGS. 2-6 thatgenerate receiver weights may also apply to the computation of thetransmitter weights. Note that the weights that control the gain andphase of each receive chain may be a function of time and may beadaptively updated with each new channel estimate. Alternatively, forsystems where the channel may vary slowly with time, weights for eachnew channel matrix do not have to be computed from scratch. Rather, theprevious weight may be adjusted using an adaptive filter. By way ofexample, a Recursive Least Squares (RLS) filter (not shown) may simplifythe digital SVD algorithm and reduce the length of computing time thatis necessary to update the weights. Further, the compensating correctionvalue may be based on the Minimum Mean-Squared Error (MMSE) algorithm(process 660).

[0032] It should be noted that the antenna weights may be complex,purely real, or purely imaginary. The weights are complex numbers ascomputed by processor 68 in the digital baseband domain. The complexweights take into account the entire impulse response of the channel,and thereby, combine and compensate for channel multi-path. In order toreduce implementation complexity and cost, purely real weights may beused with some loss in performance (the optimal real weights are thereal part of the optimal complex weights). The weights may beimplemented as tapped-delay line filters, Where the number of taps oneach antenna may be one or more. The complex weights on all taps andantennas may be controlled digitally. The number of taps on each antennamay be increased to allow better equalization of the temporal signal inthe presence of Intersymbol Interference (ISI).

[0033] By now it should be clear that the present invention providesweights that take into account the effects of colored noise, co-channelinterference, and inter-sample interference. The described method ofweight computation for analog combining architectures considers thetotal channel impulse response over a block of time. Furthermore, theseweights may also be computed to take into consideration co-channelinterference or co-channel users in the same frequency band. Byincorporating multiple antenna, variable-gain amplifiers, phase-shiftersand an RF combiner at the receiver, the present invention providessignificant gains in performance. The present invention also provides alow cost solution and reduced power consumption when compared to fullydigital systems with multiple antenna.

[0034] While certain features of the invention have been illustrated anddescribed herein, many modifications, substitutions, changes, andequivalents will now occur to those skilled in the art. It is,therefore, to be understood that the appended claims are intended tocover all such modifications and changes as fall within the true spiritof the invention.

What is claimed is:
 1. A method, comprising: computing weights foranalog signals from multiple antenna elements of a receiver that combinemulti-path signals and inter-sample interference.
 2. The method of claim1 wherein computing weights includes: using quadrature signals derivedfrom the analog signals to form a first matrix H; forming a secondmatrix H* by multiplying the first matrix H with a conjugate transposeof the first matrix H; and performing a Singular Value Decomposition(SVD) algorithm on the matrix HH*.
 3. The method of claim 1 whereincomputing weights includes: using quadrature signals derived from theanalog signals to form a first matrix H; averaging the first matrix H togenerate a second matrix Ha; and performing the Singular ValueDecomposition (SVD) algorithm on the second matrix Ha.
 4. The method ofclaim 1 wherein computing weights includes: using quadrature signalsderived from the analog signals to form a first matrix H; forming amatrix N based on colored noise estimates; forming a new matrix bymultiplying the matrix N with a conjugate transpose N*; computing thesquare root of NN*; pre and post multiplying the first matrix H by aninverse of a square root of NN* to provide a resulting matrix; andperforming a Singular Value Decomposition (SVD) algorithm on theresulting matrix.
 5. The method of claim 1 wherein computing weightsincludes: using quadrature signals to estimate interference and noise inchannels in the absence of the analog signals to form a matrix N; andusing an iterative algorithm on the matrix N.
 6. The method of claim 1further comprising: controlling a gain of a Low Noise Amplifier in areceive chain with the computed weights.
 7. The method of claim 1further comprising: controlling a phase of a phase shifter in a receivechain with the computed weights.
 8. The method of claim 1 furthercomprising: controlling a phase of a phase shifter and a gain of a poweramplifier in a transmitter with the computed weights.
 9. A method,comprising: sending known symbols to a receiver having multiple antennato derive a compensating correction value that may be applied to areceiver chain that corresponds to each antenna.
 10. The method of claim9 further including: computing weights for beam-forming analog signalsthrough the multiple antenna at the receiver that combines multi-pathsignals and inter-sample interference.
 11. The method of claim 9 furtherincluding: estimating a channel impulse response in a time-domain toprovide the compensating correction value as an analog value.
 12. Themethod of claim 9 further including: controlling signal amplificationprovided by a Low Noise Amplifier and phase through a phase shifter in areceive chain with the compensating correction value.
 13. The method ofclaim 9 further comprising: controlling a phase of a phase shifter and again of a power amplifier in a transmitter with the compensatingcorrection value.
 14. A system comprising: a Static Random Access Memory(SRAM); a communication processor coupled via an external bus to theSRAM, where the communication processor receives modulated signals atmultiple antenna and computes a compensating correction value for analogsignals from multiple antenna elements that combine multi-path signalsand inter-sample interference; and amplifier circuits in a receiver toreceive the modulated signals and further receiving the compensatingcorrection value.
 15. The system of claim 14, further including: phaseshifters in the receiver that are coupled to the amplifier circuits,wherein the phase shifters receive the compensating correction value.16. The system of claim 14, further including: power amplifiers in atransmitter to receive the compensating correction value, wherein thepower amplifiers provide gain to signals transmitted from the multipleantenna elements.
 17. A method of computing a compensating correctionvalue for analog signals from multiple antenna elements, comprising:using quadrature signals derived from the analog signals to estimateinterference and noise in channels; and using the quadrature signals toform a matrix H.
 18. The method of claim 17, further comprising: forminga matrix K based on colored noise estimates; forming a new matrix KK* bymultiplying the matrix K with a conjugate transpose K*; and computing asquare root of the new matrix KK*.
 19. The method of claim 18, furthercomprising: pre and post multiplying the matrix H by an inverse of thesquare root of KK* to provide a resulting matrix.
 20. The method ofclaim 19, further comprising: performing a Singular Value Decomposition(SVD) algorithm on the resulting matrix to generate the compensatingcorrection value.
 21. The method of claim 17, further comprising:forming a matrix K based on colored noise estimates; and generating thecompensating correction value based on the Minimum Mean-Squared Error(MMSE) algorithm.
 22. The method of claim 17, further comprising:forming a matrix O based on interference and noise in the channels inthe absence of any signal; forming a new matrix OO* by multiplying thematrix O with a conjugate transpose O*; and computing a square root ofthe new matrix OO*.
 23. The method of claim 22, further comprising: preand post multiplying the matrix H by an inverse of the square root ofOO* to provide a resulting matrix.
 24. The method of claim 23, furthercomprising: performing a Singular Value Decomposition (SVD) algorithm onthe resulting matrix to generate the compensating correction value. 25.The method of claim 17, further comprising: forming a matrix O based oninterference and noise in the channels in the absence of any signal; andcomputing the compensating correction value based on the MinimumMean-Squared Error (MMSE) algorithm.
 26. The method of claim 17, furthercomprising: forming a matrix T based on user interference in a SpatialDivision Multiple Access (SDMA) communications network; forming a newmatrix TT* by multiplying the matrix T with a conjugate transpose T*;and computing a square root of the new matrix TT*.
 27. The method ofclaim 26, further comprising: pre and post multiplying the matrix H byan inverse of the square root of TT* to provide a resulting matrix. 28.The method of claim 27, further comprising: performing a Singular ValueDecomposition (SVD) algorithm on the resulting matrix to generate thecompensating correction value.
 29. The method of claim 17, furthercomprising: forming a matrix T based on user interference in a SpatialDivision Multiple Access (SDMA) communications network; and computingthe compensating correction value based on the Minimum Mean-SquaredError (MMSE) algorithm.